advanced analytics; artificial intelligence; data governance; digital governance; fraud detection; Computer Science (miscellaneous); Artificial Intelligence; Social Sciences (miscellaneous); Public Administration; General Earth and Planetary Sciences; General Environmental Science
Abstract :
[en] The use of artificial intelligence and algorithmic decision-making in public policy processes is influenced by a range of diverse drivers. This article provides a comprehensive view of 13 drivers and their interrelationships, identified through empirical findings from the taxation and social security domains in Belgium. These drivers are organized into five hierarchical layers that policy designers need to focus on when introducing advanced analytics in fraud detection: (a) trust layer, (b) interoperability layer, (c) perceived benefits layer, (d) data governance layer, and (e) digital governance layer. The layered approach enables a holistic view of assessing adoption challenges concerning new digital technologies. The research uses thematic analysis and interpretive structural modeling.
Disciplines :
Political science, public administration & international relations
Author, co-author :
Tan, Evrim ; Public Governance Institute, KU Leuven, Leuven, Belgium
Petit Jean, Maxime; High Strategic Council, Walloon Government, Namur, Belgium
Simonofski, Anthony ; Department of Management Sciences, UNamur, Namur, Belgium
Tombal, Thomas; Tilburg Law and Economic Center (TILEC), Tilburg Institute for Law, Technology, and Society, Tilburg, Netherlands
Kleizen, Bjorn; Political Sciences Department, UAntwerpen, Antwerp, Belgium
This work was supported by the Belgian Federal Science Policy Office (BELSPO) under research grant B2/191/P3/DIGI4FED. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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